MAHMOUD NAGY - JUNE 2022
import pandas as pd
import os
pd.set_option('display.max_columns', 500)
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.ticker as tkr
import seaborn as sb
import matplotlib.dates as mdates
import plotly.express as px
import plotly.graph_objects as go
import pickle
import re
import warnings
import datetime
warnings.filterwarnings('ignore')
sb.set_style("darkgrid")
%matplotlib inline
import plotly.io as pio
pio.renderers
# pio.renderers.default = "svg"
svg_renderer = pio.renderers["svg"]
svg_renderer.width = 950
svg_renderer.height = 550
# To Apply helpers updates without resarting the kernel
import importlib
import helpers
importlib.reload(helpers)
from load_data import *
# # To keep track of any module updates
# %load_ext autoreload
# %autoreload2
%config InlineBackend.figure_format = 'retina'
print(tweets.shape)
tweets.head(1)
(1720317, 31)
| n_statuses | created_at | user_description | user_created_at | user_id | username | is_verified | user_location | n_followers | user_url | lang | profile_banner_url | profile_image_url | text | n_friends | tweet_id | user_screen_name | date | year | month | dayofmonth | hour | diff | days_diff | minutes_diff | retweet_count | reply_count | like_count | quote_count | total_retweets | tweets_interactions | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 59595 | 2018-01-01 00:21:13 | today in #3Dprint\n#hadronscollider\n#medtech\... | 2016-07-09 16:08:42 | 751810315759693824 | americaearnmoney | False | america | 5983 | NaN | en | https://pbs.twimg.com/profile_banners/75181031... | http://pbs.twimg.com/profile_images/7518904223... | tv news: amber heard and elon musk are spendin... | 6021 | 947623710281871360 | americearnmoney | 2018-01-01 | 2018 | Jan | 1 | 0 | 540 days 08:12:31 | 540 | 492.52 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
print(youtube_comments.shape)
youtube_comments.head(1)
(6251459, 21)
| video_id | comment_etag | comment_id | text | username | author_ch_id | nlikes | p_dtime | u_dtime | nreplies | snippet.topLevelComment.snippet.moderationStatus\r | comment_reply | parent_id | author_ch_url | author_profile_image | moderation_status | date | year | month | dayofmonth | hour | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 108078 | wT3RhIJZu4k | k3aisQ61gTt1ShrvAOZM2hF2TLA | Ugwoqs1OcEGmGAdARJF4AaABAg | wow that's what i call a master! after every s... | Shakera Williams | UCRPA3NvO8zjCBJVbeg-QPmw | 0 | 2018-01-01 00:31:41+00:00 | 2018-01-01T00:31:41Z | 0 | \r | comment | none | none | none | NaN | 2018-01-01 | 2018 | Jan | 1 | 0 |
print(youtube_videos.shape)
youtube_videos.head(1)
(7360, 22)
| etag | id | p_dtime | ch_id | title | description | ch_title | snippet.tags | category | language | audio_language | contentDetails.duration | is_licensed | n_views | n_likes | n_comments | date | year | month | dayofmonth | hour | youtube_videos_interactions | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 7078 | IYKu2Dsjy0k394xABy13omQUVdU | eNmYd42UYHg | 2018-01-01 09:23:04+00:00 | UChJk7sDal5ajRRtx15hxMEA | Amber Heard And Elon Musk Vacation Together In... | Amber Heard And Elon Musk Vacation Together In... | The Gossip Story | ['amber heard and elon musk back together', 'a... | People & Blogs | en-US | NaN | PT2M20S | False | 93.0 | 2.0 | 0.0 | 2018-01-01 | 2018 | Jan | 1 | 9 | 95.0 |
print(instagram_comments.shape)
instagram_comments.head(1)
(1434395, 19)
| message | datetime | id | n_replies | n_likes | media_id | parent_id | user_id | username | is_verified | account_url | year | month | dayofmonth | date | hour | clean_text | tokens | instagram_comments_interactions | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 686542 | 見とれますね(笑)😁❗ | 2018-01-14 12:14:02 | 17893409533187748 | 1.0 | 1.0 | 1692013694866470912 | n | 6115944446 | hiro.68.9.29 | False | https://www.instagram.com/hiro.68.9.29 | 2018 | Jan | 14 | 2018-01-14 | 12 | 見とれますね(笑)❗ | {'見とれますね', '笑'} | 2.0 |
# print(reddit_contributions.reset_index(drop=True).permalink.iloc[11])
# reddit_contributions.reset_index(drop=True).head(20)
print(reddit_contributions.shape)
reddit_contributions.head(1)
(177384, 30)
| child_id | permalink | text | parent_id | subreddit | created_at | sentiment_blob | sentiment_nltk | score | top_level | submission_comment | submission_text | removed_deleted | user_name | has_verified_email | is_mod | is_gold | is_banned | comment_karma | link_karma | user_created_at | banned_unverified | creation_year | diff | days_after_creation | year | date | month | dayofmonth | hour | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | t1_ds0ns4c | /r/JerkOffToCelebs/comments/7nbhsf/amber_heard... | She is giving you that look to put it in her a... | t3_7nbhsf | r/JerkOffToCelebs | 2018-01-01 00:14:23 | Neutral | Positive | 8.0 | submission | comment | amber_heard_would_be_such_a_dirty_slut_in_bed | others | Contractzzz95 | False | False | False | False | 2465.0 | 846.0 | 2017-02-09 09:52:42 | unverified | others | 325 days 14:21:41 | 325.0 | 2018 | 2018-01-01 | Jan | 1 | 0 |
reddit_contributions_score = upvotes - downvotes (for the comment or submission)| Platform | Color |
|---|---|
| Blue | |
| YouTube | Orange |
| Green | |
| Red |
CrossPlatforms Contributions TimeSeries¶
df_days = df_creations.groupby('date')['n_tweets', "youtube_comments", "instagram_comments", 'reddit_contributions'].sum().reset_index()
# df_days.head()
Note
- Twitter and Youtube have the most peaks in 2022
fig, ax = plt.subplots(figsize=(15,8))
plt.plot(df_days['date'], df_days["youtube_comments"], label="#YouTube_Comments");
plt.plot(df_days['date'], df_days["n_tweets"], label="#Tweets");
plt.plot(df_days['date'], df_days["instagram_comments"], label="#instagram_comments");
plt.plot(df_days['date'], df_days["reddit_contributions"], label="#reddit_contributions");
plt.ylabel('Contributions')
plt.title("CrossPlatforms Contributions TimeSeries", fontsize=18)
# ax.yaxis.set_major_formatter(tkr.FuncFormatter(lambda y, pos: '{:,.0f}'.format(y/1000) + 'K'))
ax.yaxis.set_major_formatter(tkr.EngFormatter())
plt.legend();
fig, ax = plt.subplots(figsize=(15,8))
plt.plot(df_days['date'], df_days["n_tweets"], label="#Tweets");
plt.plot(df_days['date'], df_days["youtube_comments"], label="#YouTube_Comments");
plt.plot(df_days['date'], df_days["instagram_comments"], label="#instagram_comments");
plt.plot(df_days['date'], df_days["reddit_contributions"], label="#reddit_contributions");
plt.ylabel('Contributions')
plt.title("CrossPlatforms Contributions TimeSeries", fontsize=18)
# ax.yaxis.set_major_formatter(tkr.FuncFormatter(lambda y, pos: '{:,.0f}'.format(y/1000) + 'K'))
ax.yaxis.set_major_formatter(tkr.EngFormatter())
plt.legend();
CrossPlatforms Contributions over Years¶
df_years = df_creations.groupby('year')['n_tweets', "youtube_comments", "instagram_comments", 'reddit_contributions'].sum().reset_index()
df_years2 = df_years.copy()
for col in ['n_tweets', "youtube_comments", "instagram_comments", 'reddit_contributions']:
df_years2[col] = df_years2[col].apply(lambda x: f'{x/1000000000:.1f}B' if x/1000000000>=1 else f'{x/1000000:.1f}M' if x/1000000>=1 else f'{x/1000:.1f}K' if x/10000>=1 else f'{x}')
df_years2
| year | n_tweets | youtube_comments | instagram_comments | reddit_contributions | |
|---|---|---|---|---|---|
| 0 | 2018 | 37.2K | 34.8K | 214.0K | 6993.0 |
| 1 | 2019 | 94.3K | 25.6K | 288.8K | 23.7K |
| 2 | 2020 | 612.6K | 351.2K | 578.6K | 128.4K |
| 3 | 2021 | 478.9K | 249.4K | 352.9K | 18.3K |
| 4 | 2022 | 497.3K | 5.6M | 0.0 | 0.0 |
x_axis = df_years["year"]
fig, ax = plt.subplots(figsize=(15,8))
plt.bar(x_axis - 0.15, df_years["n_tweets"], width=0.1, label="#Tweets");
plt.bar(x_axis - 0.05, df_years["youtube_comments"], width=0.1, label="#YouTube_Comments");
plt.bar(x_axis + 0.05, df_years["instagram_comments"], width=0.1, label="#instagram_comments");
plt.bar(x_axis + 0.15, df_years["reddit_contributions"], width=0.1, label="#reddit_contributions");
plt.ylabel('Contributions')
plt.title("CrossPlatforms Contributions over Years", fontsize=18)
# ax.yaxis.set_major_formatter(tkr.FuncFormatter(lambda y, pos: '{:,.0f}'.format(y/1000) + 'K'))
ax.yaxis.set_major_formatter(tkr.EngFormatter())
plt.legend();
CrossPlatforms Contributions over Months¶
tmp = df_creations.groupby(['month', 'year'])['n_tweets', "youtube_comments", 'instagram_comments', 'reddit_contributions'].sum().reset_index()
df_month = tmp.melt(id_vars=['month', 'year'], var_name='type', value_name='contributions')
df_month.head(1)
| month | year | type | contributions | |
|---|---|---|---|---|
| 0 | Apr | 2018 | n_tweets | 1661.0 |
## Youtube and Twitter
# df_month_yt = df_month[df_month.type.isin(['n_tweets', "youtube_comments"])]
# helpers.months_cross(df_month_yt, x="month", y="contributions", facet_on='year', n_col=2, fs=10, loc=-0.19)
helpers.months_cross(df_month, x="month", y="contributions", facet_on='year', n_col=2, fs=10, loc=-0.19)
df_month_18 = df_month[df_month['year']==2018]
df_month_19 = df_month[df_month['year']==2019]
df_month_20 = df_month[df_month['year']==2020]
df_month_21 = df_month[df_month['year']==2021]
df_month_22 = df_month[df_month['year']==2022]
importlib.reload(helpers)
<module 'helpers' from '/Users/mnagy99/jupyter/AH/Cross Platforms/SNA-AH-Cross-Platforms/helpers.py'>
helpers.months_cross(df_month_18, x="month", y="contributions", facet_on='year',
n_col=1, h=8, loc=-0.13, ratio=2, fs=14, year_str='2018')
helpers.months_cross(df_month_19, x="month", y="contributions", facet_on='year',
n_col=1, h=8, loc=-0.13, ratio=2, fs=14, year_str='2019')
helpers.months_cross(df_month_20, x="month", y="contributions", facet_on='year',
n_col=1, h=8, loc=-0.13, ratio=2, fs=14, year_str='2020')
helpers.months_cross(df_month_21, x="month", y="contributions", facet_on='year',
n_col=1, h=8, loc=-0.13, ratio=2, fs=14, year_str='2021')
helpers.months_cross(df_month_22, x="month", y="contributions", facet_on='year',
n_col=1, h=8, loc=-0.13, ratio=2, fs=14, year_str='2022')
CrossPlatforms Contributions over Days¶
tmp = df_creations.groupby(['month', 'year', 'dayofmonth'])['n_tweets', "youtube_comments", 'instagram_comments', 'reddit_contributions'].sum().reset_index()
df_days2 = tmp.melt(id_vars=['month', 'year', 'dayofmonth'], var_name='type', value_name='contributions')
df_days2.head(1)
| month | year | dayofmonth | type | contributions | |
|---|---|---|---|---|---|
| 0 | Apr | 2018 | 1 | n_tweets | 33.0 |
df_days_18 = df_days2[df_days2['year']==2018]
df_days_19 = df_days2[df_days2['year']==2019]
df_days_20 = df_days2[df_days2['year']==2020]
df_days_21 = df_days2[df_days2['year']==2021]
df_days_22 = df_days2[df_days2['year']==2022]
# importlib.reload(helpers)
helpers.days_cross(df_days_18, x="dayofmonth", y="contributions", facet_on='month', n_col=2, h=7, loc=-0.135,
ratio=1.3, fs=16, year_str='2018')
helpers.days_cross(df_days_19, x="dayofmonth", y="contributions", facet_on='month', n_col=2, h=7, loc=-0.135,
ratio=1.3, fs=16, year_str='2019')
helpers.days_cross(df_days_20, x="dayofmonth", y="contributions", facet_on='month', n_col=2, h=7, loc=-0.135,
ratio=1.3, fs=16, year_str='2020')
helpers.days_cross(df_days_21, x="dayofmonth", y="contributions", facet_on='month', n_col=2, h=7, loc=-0.135,
ratio=1.3, fs=16, year_str='2021')
helpers.days_cross(df_days_22, x="dayofmonth", y="contributions", facet_on='month', n_col=2, h=7, loc=-0.135,
ratio=1.3, fs=16, year_str='2022')
| Platform | Interactions |
|---|---|
| total_retweets + reply_count + like_count | |
| YouTube | n_views + n_likes + n_comments |
| n_replies + n_likes | |
| reddit_contributions_score (Upvotes - Downvotes) |
Note
- We don't have 'favorite_count' in the twitter metrics data (from kaggle)
- But we have it for the 5 months data that Adel rescraped
- New YouTube data don't have dislikes, as YouTube disabled the "dislike feature".
- Youtube was separated from the interactions comparison (since it has way larger values than others)
CrossPlatforms Interactions TimeSeries¶
df_days_inter = df_creations.groupby('date')['tweets_interactions', "youtube_videos_interactions", "instagram_comments_interactions", 'reddit_contributions_score'].sum().reset_index()
# df_days_inter.head()
fig, ax = plt.subplots(figsize=(15,8))
plt.plot(df_days_inter['date'], df_days_inter["tweets_interactions"],
label="#tweets_interactions", color="tab:blue");
# plt.plot(df_days_inter['date'], df_days_inter["youtube_videos_interactions"], label="#youtube_videos_interactions");
plt.plot(df_days_inter['date'], df_days_inter["instagram_comments_interactions"],
label="#instagram_comments_interactions", color="cyan");
plt.plot(df_days_inter['date'], df_days_inter["reddit_contributions_score"],
label="#reddit_contributions_score", color="tab:red");
plt.ylabel('interactions')
plt.title("CrossPlatforms Interactions TimeSeries", fontsize=18)
# ax.yaxis.set_major_formatter(tkr.FuncFormatter(lambda y, pos: '{:,.0f}'.format(y/1000) + 'K'))
ax.yaxis.set_major_formatter(tkr.EngFormatter())
plt.legend();
fig, ax = plt.subplots(figsize=(15,8))
plt.plot(df_days_inter['date'], df_days_inter["youtube_videos_interactions"],
label="#youtube_videos_interactions", color="tab:orange");
plt.plot(df_days_inter['date'], df_days_inter["tweets_interactions"],
label="#tweets_interactions", color="tab:blue");
plt.ylabel('interactions')
plt.title("CrossPlatforms Interactions TimeSeries", fontsize=18)
# ax.yaxis.set_major_formatter(tkr.FuncFormatter(lambda y, pos: '{:,.0f}'.format(y/1000) + 'K'))
ax.yaxis.set_major_formatter(tkr.EngFormatter())
plt.legend();
CrossPlatforms Interactions over Years¶
df_years_inter = df_creations.groupby('year')['tweets_interactions', "youtube_videos_interactions", "instagram_comments_interactions", 'reddit_contributions_score'].sum().reset_index()
df_years_inter2 = df_years_inter.copy()
for col in ['tweets_interactions', "youtube_videos_interactions", "instagram_comments_interactions", 'reddit_contributions_score']:
df_years_inter2[col] = df_years_inter2[col].apply(lambda x: f'{x/1000000000:.1f}B' if x/1000000000>=1 else f'{x/1000000:.1f}M' if x/1000000>=1 else f'{x/1000:.1f}K' if x/10000>=1 else f'{x}')
df_years_inter2
| year | tweets_interactions | youtube_videos_interactions | instagram_comments_interactions | reddit_contributions_score | |
|---|---|---|---|---|---|
| 0 | 2018 | 355.4K | 44.4M | 423.8K | 254.4K |
| 1 | 2019 | 1.5M | 31.6M | 626.8K | 564.5K |
| 2 | 2020 | 11.8M | 129.4M | 3.9M | 3.8M |
| 3 | 2021 | 8.6M | 119.7M | 1.8M | 437.0K |
| 4 | 2022 | 27.9M | 3.2B | 0.0 | 0.0 |
x_axis = df_years["year"]
fig, ax = plt.subplots(figsize=(15,8))
plt.bar(x_axis - 0.15, df_years_inter["tweets_interactions"], width=0.1,
label="#tweets_interactions", color="tab:blue");
# plt.bar(x_axis - 0.05, df_years_inter["youtube_videos_interactions"], width=0.1, label="#youtube_videos_interactions");
plt.bar(x_axis + 0.05, df_years_inter["instagram_comments_interactions"], width=0.1,
label="#instagram_comments_interactions", color="tab:green");
plt.bar(x_axis + 0.15, df_years_inter["reddit_contributions_score"], width=0.1,
label="#reddit_contributions_score", color="tab:red");
plt.ylabel('Interactions')
plt.title("CrossPlatforms Interactions over Years", fontsize=18)
# ax.yaxis.set_major_formatter(tkr.FuncFormatter(lambda y, pos: '{:,.0f}'.format(y/1000) + 'K'))
ax.yaxis.set_major_formatter(tkr.EngFormatter())
plt.legend();
x_axis = df_years["year"]
fig, ax = plt.subplots(figsize=(15,8))
plt.bar(x_axis - 0.15, df_years_inter["tweets_interactions"], width=0.1,
label="#tweets_interactions", color="tab:blue");
plt.bar(x_axis - 0.05, df_years_inter["youtube_videos_interactions"], width=0.1,
label="#youtube_videos_interactions", color="tab:orange");
plt.ylabel('Interactions')
plt.title("CrossPlatforms Interactions over Years", fontsize=18)
# ax.yaxis.set_major_formatter(tkr.FuncFormatter(lambda y, pos: '{:,.0f}'.format(y/1000) + 'K'))
ax.yaxis.set_major_formatter(tkr.EngFormatter())
plt.legend();
CrossPlatforms Interactions over Months¶
tmp = df_creations.groupby(['month', 'year'])['tweets_interactions', "instagram_comments_interactions", 'reddit_contributions_score'].sum().reset_index()
df_month_inter = tmp.melt(id_vars=['month', 'year'], var_name='type', value_name='interactions')
df_month_inter.head(1)
| month | year | type | interactions | |
|---|---|---|---|---|
| 0 | Apr | 2018 | tweets_interactions | 14185.0 |
helpers.months_cross(df_month_inter, x="month", y="interactions", facet_on='year', n_col=2, loc=-0.21,
year_str='Twitter | Instagram | Reddit', fs=12, c=['tab:blue', 'tab:green', 'tab:red'])
importlib.reload(helpers)
<module 'helpers' from '/Users/mnagy99/jupyter/AH/Cross Platforms/SNA-AH-Cross-Platforms/helpers.py'>
tmp = df_creations.groupby(['month', 'year'])['youtube_videos_interactions'].sum().reset_index()
df_month_inter2 = tmp.melt(id_vars=['month', 'year'], var_name='type', value_name='interactions')
helpers.months_cross(df_month_inter2, x="month", y="interactions", facet_on='year', n_col=2,
year_str='YouTube Videos', fs=12, c=['tab:orange'], loc=-0.21)
df_month_inter_18 = df_month_inter[df_month_inter['year']==2018]
df_month_inter_19 = df_month_inter[df_month_inter['year']==2019]
df_month_inter_20 = df_month_inter[df_month_inter['year']==2020]
df_month_inter_21 = df_month_inter[df_month_inter['year']==2021]
df_month_inter_22 = df_month_inter[df_month_inter['year']==2022]
# importlib.reload(helpers)
helpers.months_cross(df_month_inter_18, x="month", y="interactions", facet_on='year', n_col=1, h=8, loc=-0.13,
ratio=2, fs=14, year_str='2018', c=['tab:blue', 'tab:green', 'tab:red'])
helpers.months_cross(df_month_inter_19, x="month", y="interactions", facet_on='year', n_col=1, h=8, loc=-0.13,
ratio=2, fs=14, year_str='2019', c=['tab:blue', 'tab:green', 'tab:red'])
helpers.months_cross(df_month_inter_20, x="month", y="interactions", facet_on='year', n_col=1, h=8, loc=-0.13,
ratio=2, fs=14, year_str='2020', c=['tab:blue', 'tab:green', 'tab:red'])
helpers.months_cross(df_month_inter_21, x="month", y="interactions", facet_on='year', n_col=1, h=8, loc=-0.13,
ratio=2, fs=14, year_str='2021', c=['tab:blue', 'tab:green', 'tab:red'])
helpers.months_cross(df_month_inter_22, x="month", y="interactions", facet_on='year', n_col=1, h=8, loc=-0.13,
ratio=2, fs=14, year_str='2022', c=['tab:blue', 'tab:green', 'tab:red'])
CrossPlatforms Interactions in Each Day¶
tmp = df_creations.groupby(['month', 'year', 'dayofmonth'])['tweets_interactions', "instagram_comments_interactions", 'reddit_contributions_score'].sum().reset_index()
df_days2_inter = tmp.melt(id_vars=['month', 'year', 'dayofmonth'], var_name='type', value_name='interactions')
df_days2_inter.head(1)
| month | year | dayofmonth | type | interactions | |
|---|---|---|---|---|---|
| 0 | Apr | 2018 | 1 | tweets_interactions | 831.0 |
df_days_inter_18 = df_days2_inter[df_days2_inter['year']==2018]
df_days_inter_19 = df_days2_inter[df_days2_inter['year']==2019]
df_days_inter_20 = df_days2_inter[df_days2_inter['year']==2020]
df_days_inter_21 = df_days2_inter[df_days2_inter['year']==2021]
df_days_inter_22 = df_days2_inter[df_days2_inter['year']==2022]
# importlib.reload(helpers)
helpers.days_cross(df_days_inter_18, x="dayofmonth", y="interactions", facet_on='month', n_col=2, h=7, loc=-0.14,
ratio=1.3, fs=16, year_str='2018', c=['tab:blue', 'tab:green', 'tab:red'])
helpers.days_cross(df_days_inter_19, x="dayofmonth", y="interactions", facet_on='month', n_col=2, h=7, loc=-0.14,
ratio=1.3, fs=16, year_str='2019', c=['tab:blue', 'tab:green', 'tab:red'])
helpers.days_cross(df_days_inter_20, x="dayofmonth", y="interactions", facet_on='month', n_col=2, h=7, loc=-0.14,
ratio=1.3, fs=16, year_str='2020', c=['tab:blue', 'tab:green', 'tab:red'])
helpers.days_cross(df_days_inter_21, x="dayofmonth", y="interactions", facet_on='month', n_col=2, h=7, loc=-0.14,
ratio=1.3, fs=16, year_str='2021', c=['tab:blue', 'tab:green', 'tab:red'])
helpers.days_cross(df_days_inter_22, x="dayofmonth", y="interactions", facet_on='month', n_col=2, h=7, loc=-0.14,
ratio=1.3, fs=16, year_str='2022', c=['tab:blue', 'tab:green', 'tab:red'])
tweets.text.value_counts().head(10)
#justiceforjohnnydepp 79623 #amberheardisanabuser 3550 fuck amber heard 3530 #amberheardisaliar 3382 #johnnydepp \n#justiceforjohnnydepp 2369 #justiceforjohnnydepp #amberheardisanabuser 2000 #justiceforjohnnydepp ⚖️ 1570 #johnnydepp\n#justiceforjohnnydepp 1521 johnny depp \n#justiceforjohnnydepp 1437 johnny depp\n#justiceforjohnnydepp 861 Name: text, dtype: int64
youtube_comments.text.value_counts().head(10)
yes 11776 “they won’t believe you, because you are a man”\r\n\r\nshe is not a victim. 6844 “they won’t believe you, because you are a man”\n\nshe is not a victim. 6482 that's crazy 4152 lol 4013 "they won't believe you, because you are a man"\n\nshe is not a victim. 3804 #justiceforjohnnydepp 3222 justice for johnny 2943 that’s crazy 2941 😂😂😂 2347 Name: text, dtype: int64
youtube_videos.title.value_counts().head(10)
GULLY Official Trailer (2021) Amber Heard 9 GULLY Official Trailer (2021) 6 LIVE: Johnny Depp-Amber Heard defamation trial testimony | LiveNOW from FOX 5 Johnny Sparrow VS Ex Aqua Mera #shorts #ambervjohnny #johnnyvamber #amberheard #johnnydepp #verdict 5 Johnny Depp wins libel lawsuit against ex-wife Amber Heard 5 Everything Amber Heard has shared about her baby girl, Oonagh Paige 4 Amber Heard 4 Johnny Depp wins defamation case against Amber Heard 4 Amber Heard Testifies In Johnny Depp Defamation Trial | NBC News 3 WATCH LIVE | Day 21 of the Johnny Depp v Amber Heard Libel Lawsuit Trial 3 Name: title, dtype: int64
instagram_comments.clean_text.value_counts().head(10)
beautiful 7183 #justiceforjohnnydepp 4958 beautiful 4336 wow 2918 nice 2809 1 2430 2 2413 gorgeous 2154 ti amo amore 1955 ♥ 1880 Name: clean_text, dtype: int64
reddit_contributions.text.value_counts().head(10)
[deleted] 4955 Amber Heard 4103 [removed] 1941 Make sure to follow our community guidelines.\n\n**[Get user flair](https://redd.it/e0a4mn) and check out our [Instagram page](https://www.instagram.com/celebtag) for more celebrity content!**\n\n\n*I am a bot, and this action was performed automatically. Please [contact the moderators of this subreddit](/message/compose/?to=/r/Celebhub) if you have any questions or concerns.* 185 Amber 181 ### [Browse JerkOffChallenges](https://jerkofftocelebs.com/actors/) • [Browse Picture Galleries](https://jerkofftocelebs.com/pictures/) • NEW [JerkOffToGermanCelebs](https://reddit.com/r/JerkOffToGermanCelebs/)\n\n\n^(*Thank you for your submission. Make sure to follow the rules.*) \n\n^(*Check out our Website*) ^[*here*](https://jerkofftocelebs.com/). \n\n^(*Join our Discord*) ^[*here*](https://discord.gg/FMhrH2j).\n\n^(*Explore more subreddits*) ^[*here*](https://jerkofftocelebs.com/reddit-nsfw-list/).\n\n\n*I am a bot, and this action was performed automatically. Please [contact the moderators of this subreddit](/message/compose/?to=/r/JerkOffToCelebs) if you have any questions or concerns.* 176 Rule 9 overused. No Johny Depp or Amber Heard memes at this time\n\n*I am a bot, and this action was performed automatically. Please [contact the moderators of this subreddit](/message/compose/?to=/r/memes) if you have any questions or concerns.* 157 What? What did she hear? 121 Your submission has been automatically removed for not including a valid category/subcategory tag. Tags are essential to an optimal browsing experience for our users.\n\nSince your post was removed automatically, you are free to resubmit it with an appropriate tag. You can find the tagging guide [here](/r/DC_Cinematic/wiki/linkflair#wiki_automated_tagging). Add a valid and appropriate tag in your submission title. Choose wisely, as posts with misleading tags are subject to removal.\n\n**Message the moderators if your post was removed despite being tagged with an input from the category list.**\n\n\n*I am a bot, and this action was performed automatically. Please [contact the moderators of this subreddit](/message/compose/?to=/r/DC_Cinematic) if you have any questions or concerns.* 111 Amber heard 107 Name: text, dtype: int64
tweets.username.value_counts().head(10)
Libby 🐝🏴☠️🥚 #JusticeForJohnnyDepp 16145 LL 11426 Teri Carson ☠️ 🇮🇪 💀 🇨🇮 ☠️ 7150 Princess Consuela Bananahammock 5420 🍩🍉M.G. Justice For Johnny Depp⚖Wald-Mignon🦋🌞🌷 5284 Marley M 5184 Ciang385 5182 Nor33 🇫🇷 4710 good will 4664 Ewinters Wald-Mignon 4300 Name: username, dtype: int64
youtube_comments.username.value_counts().head(10)
Johnny Depp 9115 slynnc kitty 4647 eHacker 3523 LaraCroftEyes1 3114 J 1700 A 1631 Binge Central 1604 M 1416 peter pan 1222 Chris 1190 Name: username, dtype: int64
youtube_videos.ch_title.value_counts().head(10)
Law&Crime Network 325 Film Streak 268 LiveNOW from FOX 177 eHacker 109 Entertainment Tonight 94 Viral Vision 67 Popcorned Planet 66 Celebrity Craze 60 The Gossipy 51 Nerdette's NewsStand 48 Name: ch_title, dtype: int64
instagram_comments.username.value_counts().head(10)
kurilka_dzen 3987 celebx.world 3879 hannah_in.wonderland 3738 a2621010 3149 angel_amber__heard 2902 razaopetraglia 2623 erdmannleistung2 2490 ozosmanli_tesbih 1997 words_without_u 1878 sweet_and_caring_ 1685 Name: username, dtype: int64
reddit_contributions.user_name.value_counts().head(10)
-banned- 25136 AutoModerator 2670 CelebBattleVoteBot 565 5th_Law_of_Robotics 366 DerHander 279 Support_Johnny_Depp 256 fluidmoviestar 201 AutoNewsAdmin 176 gaul66 156 newsfeedmedia 140 Name: user_name, dtype: int64